The present invention relates generally to electrical resistance heaters (xe2x80x9cresistive element heatersxe2x80x9d) and more particularly to a method and apparatus for predicting the failure of said heaters.
Past efforts to develop a failure prediction system for resistive element heaters have concentrated largely on the search for a parametric method, meaning a method for detecting pending failure based on the change in a measurable parameter such as heater element electrical resistance, voltage, or current.
These methods have been unsuccessful, primarily because the rates of change of simple parameters such as resistance, although sometimes a good indicator of heater degradation, are not reliable as statistically consistent signatures of pending failure. Although sometimes a dramatic shift may be detected prior to failure, often little or no shift occurs. Oxidation of the heating element may impact the resistance, and oxidation rates can vary based on temperature and power level. Therefore, since it is typical for the temperature and power to vary dramatically under normal operational conditions, oxidation rates may also vary, making a failure prediction based solely on a measured change in resistance statistically unreliable.
Significant research and laboratory testing of resistive element heaters have been performed searching for parameters that are useful for heater failure prediction, and as a result a large database of information is available concerning the effect of various design, construction, and operating variables on resistive element heater service life. Most of the data that is available can be considered constant value, independent variables, meaning the data gathered are based on specific heater designs, operating within specific repetitive operating thermal and power profiles. Data of this nature can be useful for methods of predicting reliability for a specific heater design when service parameters, such as average sheath temperature and cycle rate are assumed.
However, the problem in using methods such as the one described above to actively predict failure during actual heater operation is that a heater is not typically operated in a specific repetitive profile, and even if a repetitive cycle is seen during actual operation, the cycle is usually complex or may vary significantly due to changes in input power, process demand and heat transfer efficiency.
As indicated above, research in this area has shown that measured heater element independent parameters are not generally practical in predicting heater failure. Often little or no shift of single given parameter occurs until the actual time of failure because of the inherent variations in the specific heater construction and their relation to the specific stresses present in the operating environment. As a result, relying on a single independent parameter results in a prediction method with low statistical accuracy. It is possible that a system that monitors many independent parameters simultaneously might improve prediction accuracy; however, such a system would require complex measurement equipment and would be cost prohibitive.
Gammaflux is a manufacturer of hot runner systems for the plastic injection molding industry. They sell a product that purports to predict resistive element heater failure, called MOLD MONITOR(copyright), which is an on-line software package to be utilized with their Series 9500 temperature control systems. The product periodically calculates the resistance of the heater element by monitoring the applied voltage and current draw of the resistive element for a change, which would indicate a heater resistance shift. However, as noted earlier, this method is not effective for detecting many heater failure modes. Unless the prediction method consistently predicts the majority of failure types, its usefulness is severely limited.
U.S. Pat. No. 5,736,930 issued Apr. 07, 1998 to Cappels addresses failure prediction of an apparatus similar to that of a heater element. This patent addresses failure prediction of a radiation source and more specifically a lamp or bulb for an overhead projector or the like. The similarity between the type of apparatus shown in Cappels for which failure is predicted and a resistive element heater that the present invention addresses is that they both involve current carrying elements. In Cappels the objective of the apparatus is to generate light, whereas in the subject invention, generation of heat is the objective. However, Cappels ""930 does not utilize resistance as a key to monitor performance. Cappels measures radiance over time. This method may be effective for a radiating light source element such as is found in an overhead projector because the light source is either fully on or fully off with little or no input power variation when fully on. Therefore by monitoring the radiance output of a light source of this type should allow for prediction of failure. However, in the case of resistive element heaters, the method of Cappels will be ineffective because heater elements are very inefficient light producers even in the IR light spectrum. Thus, radiance sensors would not be effective in providing relevant information for predicting failure of a resistive element heater.
A more effective method is therefore needed to predict the failure of resistive element heaters.
It is in view of the above problems that the present invention was developed.
The invention thus has as an object to provide a system that can predict the failure and/or reliability of a resistive element heater.
The present invention involves a system that utilizes a method for predicting the failure of a resistive element heater and estimating service life consumed by using a known set of thermo-physical properties related to device construction parameters and measured operating characteristics.
The system actively correlates a laboratory generated database of variables that affect heater life, derived with respect to a baseline heater design and construction, to an actual thermal profile measured during heater service operation, or that correlates the variables to a predicted normalized thermal profile. Lab testing determines the operative design and construction variables present in a given heater and how these variables affect heater life. An eminent failure for a given heater is predicted by a method of monitoring temperature related stress that a given heater is subjected to. These stress events are then correlated to the historical life data for selected design and construction variables when subjected to similar stress events. Finally a determination is made of the stress events"" total impact on service life or ultimately the amount of service life consumed. In order to make such a prediction, first, a temperature related oxidation life factor is assigned to each stress event based on the oxidation characteristics of an element alloy type. These stress event factors are cumulative over time. Second, a ratiometric construction factor of a given heater is derived with respect to a laboratory standard heater design, thereby creating a simplified life factor performance model for the given heater construction. Finally, a measured service life factor is derived with respect to a laboratory standard heater design based on the element alloy type. These factors are utilized in combination to derive a predicted percent service life consumed and percent service life remaining for a given heater during actual operation. This prediction is considered the xe2x80x9cactive formxe2x80x9d of the invention because heater temperatures are measured during actual heater operation.
However, there is also a xe2x80x9cpassive formxe2x80x9d of the invention were total service life of a given heater design is passively predicted (no actual operating measurements taken). In the passive form, in lieu of calculating measured service time, a mean operating life factor is used, and in lieu of taking periodic temperature measurements to define the operating profile, average temperatures are predicted based on the intended service application.
The estimate of service life consumption can be used to support statistical decisions concerning the likelihood of heater failure at a given point in time and the projected service life remaining based on the historical rate of consumption. The method may be hosted in software or firmware and incorporated within a heater control scheme such that executive decisions concerning scheduled maintenance for the heater resident application can be effected. The method may also be used as a design tool to estimate the expected life of a heater in a given application for logistic support analysis or reliability prediction purposes.
It is noted above that the prior art has concentrated largely on the search for a parametric method, meaning a method for detecting pending failure based on the change in a measurable parameter such as element electrical resistance, voltage, or current. These methods have been unsuccessful mostly because the rates of change of simple parameters such as resistance, although sometimes a good indicator of heater degradation, are not reliable as statistically consistent signatures of pending failure.
However, the inventor has accumulated a large database of information concerning the effect of various design, construction, and operating variables on heater life and key parameters have been identified. The inventor has determined that on/off cycling of the heater element and the varying temperatures that the element reaches are key in predicting operating life because of the effect temperature has on the oxidation rate of a resistive heater element. By utilizing this database of information related to design and construction parameters and a given thermal profile with the above method, the consumption of heater life can be actively measured against a statistical mean for that heater type and the life remaining can be predicted with good statistical confidence and this is the key to the inventors method.